Microsoft recently announced a campaign by a sophisticated nation-state threat actor, operating from China, to exploit a collection of 0-day vulnerabilities in Microsoft Exchange and exfiltrate customer data. They’re calling the previously unknown hacking gang Hafnium. Microsoft has apparently been aware of Hafnium for a while — they do describe the group’s historical targets.
Logz.io has always prided itself as a company pushing the use of open source tech. As we have moved to expand our reach with metrics and traces over the past year and a half, we have doubled down on our own contributions to the community. With (distributed) traces in particular, we have been able to forge ahead. Our relationship with the teams at Jaeger and OpenTelemetry have really blossomed (and we are kind of proud to have supported the latter in the run-up to the OpenTelemetry v1.0 release).
One of the great things about Logz.io Log Management is that it’s based on the most popular open source logging technology out there: the ELK Stack (click here to view our thoughts and plans on the recent Elastic license). This means Logz.io users get to leverage log shipping and collector options within the rich ELK ecosystem. So how do you know which log shipping technology to use?
We can plausibly say the enterprise development market turned the tide on cloud-native development in 2020, as most net-new software and serious overhaul projects started moving toward microservices architectures, with Kubernetes as the preferred platform.
OpenTelemetry 1.0 (Otel) is finally here (in fact, 1.0.1). The announcement brings the industry closer to a standard for observability. OpenTelemetry v1.0.1 will focus solely on tracing for now, but work continues on integrations for metrics and logs. We are still a long way off from this vision becoming reality. Metrics today are in beta, and this is where the community focus is being applied. Logging is even earlier in its life lifecycle.
PromQL, short for Prometheus Querying Language, is the main way to query metrics within Prometheus. You can display an expression’s return either as a graph or export it using the HTTP API. PromQL uses three data types: scalars, range vectors, and instant vectors. It also uses strings, but only as literals. This intro will provide basic PromQL examples and concepts to understand as you get used to Prometheus queries.
We’ve all been watching closely as the Solarwinds hack, known as SUNBURST, gets its due analysis. This attack was sophisticated and rightfully should concern any company. Companies are now — or should be — considering not only what products they are using but to what attack vectors those products are exposed that unduly extend attack surfaces. Solarwinds makes great products — I’ve used them for years.
These days, more and more web applications are developed and refined to keep the customer engagement at the highest level possible. It is crucial to provide a smooth experience to the customer hence monitoring is of paramount importance. One key factor in that is monitoring the web server we use. In this article, we will explore Logz.io features by monitoring an Apache Web Server.
